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The skills to transfer data between external systems and your cluster. This includes the following:
- Import data from a MySQL database into HDFS using Sqoop
- Export data to a MySQL database from HDFS using Sqoop
- Change the delimiter and file format of data during import using Sqoop
- Ingest real-time and near-real-time streaming data into HDFS
- Process streaming data as it is loaded onto the cluster
- Load data into and out of HDFS using the Hadoop File System commands
- Transform, Stage, and Store
Convert a set of data values in a given format stored in HDFS into new data values or a new data format and write them into HDFS.
- Load RDD data from HDFS for use in Spark applications
- Write the results from an RDD back into HDFS using Spark
- Read and write files in a variety of file formats
- Perform standard extract, transform, load (ETL) processes on data
- Data Analysis
Use Spark SQL to interact with the metastore pro-grammatically in your applications. Generate reports by using queries against loaded data.
- Use metastore tables as an input source or an output sink for Spark applications
- Understand the fundamentals of querying datasets in Spark
- Filter data using Spark
- Write queries that calculate aggregate statistics
- Join disparate datasets using Spark
- Produce ranked or sorted data
This is a practical exam and the candidate should be familiar with all aspects of generating a result, not just writing code.
- Supply command-line options to change your application configuration, such as increasing available memory